Too Technical for Analysts, Too Business-Driven for Engineers
- Liudmyla Taranenko
- Jun 30
- 1 min read
I recently tried to hire a Data Analytics Engineer, and it became clear that this niche is still poorly defined in the industry.
We were honest from the start: this person should write better code than an analyst, and think more analytically and contextually than an engineer.
We weren't looking for a unicorn. We were simply looking for someone who:
Writes more structured and maintainable code than a typical data analyst
Brings more business understanding and critical thinking than a typical data engineer
Can independently explore a task and domain before asking, “What should I do next?”
But the reality of the market was:
- We mostly saw analysts with weak Python/SQL foundations
- Or engineers who didn't grasp the "why" behind the data
The biggest challenge is when people don't even try to understand the business meaning of the data.
We need people who go beyond querying tables, who understand the why, model reality accurately, and turn messy data into actionable systems.
The Data Analytics Engineer role deserves more attention. It’s not just a blend, it's a mindset.
I truly believe this is one of the most valuable and underrated roles in a modern data team.
If you're someone who enjoys both thinking and building, if you like asking "why" before jumping to "how", this space is for you.
And if you're building a team: don't just look for analysts and engineers.
Start looking for the people in between, the ones who think in systems, who care about clarity, who want to bring structure to ambiguity.
They might not come with the exact title, but when you find them, they'll transform your data function.
